code: def call(self, inputs):
      x, a = inputs
      x = self.conv1([x, a])
      x = self.conv2([x, a])
      output = self.flatten(x)
      output = self.fc1(output)
      output = self.fc2(output)
  
      return output
  
file_path: spektral/examples/other/graph_signal_classification_mnist.py
imports: import numpy
  import tensorflow
  from tensorflow.keras import Model
  from tensorflow.keras.layers import Dense
  from tensorflow.keras.losses import SparseCategoricalCrossentropy
  from tensorflow.keras.metrics import sparse_categorical_accuracy
  from tensorflow.keras.optimizers import Adam
  from tensorflow.keras.regularizers import l2
  from spektral.data import MixedLoader
  from spektral.datasets.mnist import MNIST
  from spektral.layers import GCNConv, GlobalSumPool
  from spektral.utils.sparse import sp_matrix_to_sp_tensor
label_desc: Use image node_id 2 for calling the Net obj's underlying member method code with example usage: obj.call(inputs) and returns: output